Who (or What) Do You Trust? Data Survey Asks

George Leopold

(EtiAmmos/Shutterstock)

The combination of high-profile data breaches and the rise of machines involved in decision-making is undermining trust in big data and the analytics behind business decisions, warns a new study of the “evolving nature of trust in the digital world.”

The examination released this week by business consultant KPMG International declares: “Trust is now a defining factor in an organization’s success or failure.” Specifically, trust is about the ability to bet the company on the data and analytics behind decision-making tools, the consultant said.

While nearly two-thirds of CEOs polled by KPMG listed “trust” as a high priority, only 35 percent said they had high confidence in their organization’s analytics capabilities. Hence, the report continues, corporate executives “will need to manage machines as rigorously as they manage their people.”

That requirement has given rise to what KPMG bills as “trusted analytics,” while raising the issue of responsibility for managing the technology. “With so much riding on the output of data and analytics, significant questions are now emerging about the trust placed in the data, the analytics and the controls that underwrite a new way of making decisions,” the report notes.

These seeds of mistrust are providing an opening for vendors specializing in tools designed to help determine what data are stored in the company vaults and how it got there. For example, ASG Technologies, an information access, management and control vendor, touts a service that helps users track the lineage of data. The approach is promoted as building trust in data and analytics by improving governance and security, the company said.

As analytics goes mainstream with the proliferation of self-service tools, mistrust of data and analytics is likely to grow, especially as new data privacy and governance regulations kick in. For instance, companies will have to comply with the European Union’s General Data Protection Regulations whether an individual or a machine accesses private data, vendors note. The EU rules enter force in May.

Accountability is another problem, KPMG found, with most of the executives surveyed uncertain about who is responsibility when machine-based decisions leads to financial loss or worse. Most (62 percent) said responsibility rests with those managing analytics platforms while only 25 percent said the buck stopped at the CEO’s desk.

Adding to the lack of clarity underpinning data and analytics mistrust, respondents were divided on which department should be held accountable for faulty analytics: 19 percent said the CIO; 13 percent pointed a finger at the chief data officer; while only 7 percent said a data flub was the CEO’s responsibility.

The survey “is telling us that there is a tendency to absolve the core business for decisions made with machines,” said Brad Fisher, who heads KPMG’s data and analytics unit. “This is understandable given technology’s legacy as a support service….”

Added Fisher: “Many IT professionals do not have the domain knowledge or the overall capacity required to ensure trust in [data and analytics]. We believe the responsibility lies with the C-suite.”

The trusted analytics survey reinforces KPMG’s annual CEO survey released last summer that found growing concerns about where data is coming from and whether it can be trusted when making multi-million dollar decisions. Nearly half of those polled expressed doubts about the integrity of the massive data volumes they are coping with and whether they can trust it in making strategic decisions.